IU SIP CALCULATORHow This Indicator Script Works:
1. This indicator script calculate the monthly SIP returns of any market over any user defined period.
2. SIP stands for Systematic Investment Plan. It is a way to invest in any asset by regularly investing a fixed amount of money at regular intervals for example Monthly, Weekly, Quarterly etc.
3. This indicator Calculate the following
# Average buy price
# Total quantity hold
# Yearly returns
# Monthly returns
# Total invested amount
# Total profits in amount
# Total portfolio value
# Total returns in per percentage term.
4. This script takes monthly SIP amount, starting month, starting year, ending year, ending month from the user and store the value for calculations.
5. After that it store the open price of every month into an array then it average the array and compare that price with the last month close price.
6. on the bases of this it performs all of the calculations.
7. The script plot every calculation into an table from.
8. It requires monthly chart timeframe for working.
9. The table is editable user can change the color and transparency.
How User Can Benefit From The Script:
1. User can get the past monthly SIP returns of any market he wants to invest this will give him an overview about what to expect from the market.
2. Once user understand the expected returns from the market he can adjust his investment strategy.
3. This help the user to Analyse various stocks and their past performance.
4. User can also short list the best performed stocks.
5. Over all this script will give complete SIP vision of any market.
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Relative Trend Index (RTI) by Zeiierman█ Overview
The Relative Trend Index (RTI) developed by Zeiierman is an innovative technical analysis tool designed to measure the strength and direction of the market trend. Unlike some traditional indicators, the RTI boasts a distinctive ability to adapt and respond to market volatility, while still minimizing the effects of minor, short-term market fluctuations.
The Relative Trend Index blends trend-following and mean-reverting characteristics, paired with a customizable and intuitive approach to trend strength, and its sensitivity to price action makes this indicator stand out.
█ Benefits of using this RTI instead of RSI
The Relative Strength Index (RSI) and the Relative Trend Index (RTI) are both powerful technical indicators, each with its own unique strengths.
However, there are key differences that make the RTI arguably more sophisticated and precise, especially when it comes to identifying trends and overbought/oversold (OB/OS) areas.
The RSI is a momentum oscillator that measures the speed and change of price movements and is typically used to identify overbought and oversold conditions in a market. However, its primary limitation lies in its tendency to produce false signals during extended trending periods.
On the other hand, the RTI is designed specifically to identify and adapt to market trends. Instead of solely focusing on price changes, the RTI measures the relative positioning of the current closing price within its recent range, providing a more comprehensive view of market conditions.
The RTI's adaptable nature is particularly valuable. The user-adjustable sensitivity percentage allows traders to fine-tune the indicator's responsiveness, making it more resilient to sudden market fluctuations and noise that could otherwise produce false signals. This feature is advantageous in various market conditions, from trending to choppy and sideways-moving markets.
Furthermore, the RTI's unique method of defining OB/OS zones takes into account the prevailing trend, which can provide a more precise reflection of the market's condition.
While the RSI is an invaluable tool in many traders' toolkits, the RTI's unique approach to trend identification, adaptability, and enhanced definition of OB/OS zones can provide traders with a more nuanced understanding of market conditions and potential trading opportunities. This makes the RTI an especially powerful tool for those seeking to ride long-term trends and avoid false signals.
█ Calculations
In summary, while simple enough, the math behind the RTI indicator is quite powerful. It combines the quantification of price volatility with the flexibility to adjust the trend sensitivity. It provides a normalized output that can be interpreted consistently across various trading scenarios.
The math behind the Relative Trend Index (RTI) indicator is rooted in some fundamental statistical concepts: Standard Deviation and Percentiles.
Standard Deviation: The Standard Deviation is a measure of dispersion or variability in a dataset. It quantifies the degree to which each data point deviates from the mean (or average) of the data set. In this script, the standard deviation is computed on the 'close' prices over a specified number of periods. This provides a measure of the volatility in the price over that period. The higher the standard deviation, the more volatile the price has been.
Percentiles: The percentile is a measure used in statistics indicating the value below which a given percentage of observations in a group falls. After calculating the upper and lower trends for the last 'length' periods and sorting these values, the script uses the 'Sensitivity ' parameter to extract percentiles from these sorted arrays. This is a powerful concept because it allows us to adjust the sensitivity of our signals. By choosing different percentiles (controlled through the 'Sensitivity' parameter), we can decide whether we want to react only to extreme events (high percentiles) or be more reactive and consider smaller deviations from the norm as significant (lower percentiles).
Finally, the script calculates the Relative Trend Index value, which is essentially a normalized measure indicating where the current price falls between the upper and lower trend values. This simple ratio is incredibly powerful as it provides a standardized measure that can be used across different securities and market conditions to identify potential trading signals.
Core Components
Trend Data Count: This parameter denotes the number of data points used in the RTI's calculation, determining the trend length. A higher count captures a more extended market view (long-term trend), providing smoother results that are more resistant to sudden market changes. In contrast, a lower count focuses on more recent data (short-term trend), yielding faster responses to market changes, albeit at the cost of increased susceptibility to market noise.
Trend Sensitivity Percentage: This parameter is employed to select the indices within the trend arrays used for upper and lower trend definitions. By adjusting this value, users can affect the sensitivity of the trend, with higher percentages leading to a less sensitive trend.
█ How to use
The RTI plots a line that revolves around a mid-point of 50. When the RTI is above 50, it implies that the market trend is bullish (upward), and when it's below 50, it indicates a bearish (downward) trend. Furthermore, the farther the RTI deviates from the 50 line, the stronger the trend is perceived to be.
Bullish
Bearish
The RTI includes user-defined Overbought and Oversold levels. These thresholds suggest potential trading opportunities when they are crossed, serving as a cue for traders to possibly buy or sell. This gives the RTI an additional use case as a mean-reversion tool, in addition to being a trend-following indicator.
In short
Trend Confirmation and Reversals: If the percentage trend value is consistently closer to the upper level, it can indicate a strong uptrend. Similarly, if it's closer to the lower level, a downtrend may be in play. If the percentage trend line begins to move away from one trend line towards the other, it could suggest a potential trend reversal.
Identifying Overbought and Oversold Conditions: When the percentage trend value reaches the upper trend line (signified by a value of 1), it suggests an overbought condition - i.e., the price has been pushed up, perhaps too far, and could be due for a pullback, or indicating a strong positive trend. Conversely, when the percentage trend value hits the lower trend line (a value of 0), it indicates an oversold condition - the price may have been driven down and could be set to rebound, or indicate a strong negative trend. Traders often use these overbought and oversold signals as contrarian indicators, considering them potential signs to sell (in overbought conditions) or buy (in oversold conditions). If the RTI line remains overbought or oversold for an extended period, it indicates a strong trend in that direction.
█ Settings
One key feature of the RTI is its configurability. It allows users to set the trend data length and trend sensitivity.
The trend data length represents the number of data points used in the trend calculation. A longer trend data length will reflect a more long-term trend, whereas a shorter trend data length will capture short-term movements.
Trend sensitivity refers to the threshold for determining what constitutes a significant trend. High sensitivity levels will deem fewer price movements as significant, hence making the trend less sensitive. Conversely, low sensitivity levels will deem more price movements as significant, hence making the trend more sensitive.
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Disclaimer
The information contained in my Scripts/Indicators/Ideas/Algos/Systems does not constitute financial advice or a solicitation to buy or sell any securities of any type. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
My Scripts/Indicators/Ideas/Algos/Systems are only for educational purposes!
Psychological levels (Bank levels) PsychoLevels v3 - TartigradiaPsychological levels (Bank levels) plots the closest "round" price levels above and below current price, based on neuroscience research of how humans intuitively calculate in logarithms.
Psychological levels, also called bank levels, are "round" price numbers, by truncating after the nth leftmost digits, around which price often experience resistance or support, because traders and investors tend to set orders around these round numbers.
The calculation done here is fully automatic and dynamic, contrary to other similar scripts, this one uses a mathematical calculation that extracts the 1, 2 or 3 leftmost digits and calculate the previous and next level by incrementing/decrementing these digits. This means it works for any symbol under any price range.
This approach is based on neuroscience research, which found that human brains intuitively approximate numbers on a logarithmic scale, adults and children alike, and similarly to macaques, for more info see Numerical Cognition , Weber-Fechner Law , Zipf law .
For example, if price is at 0.0421, the next major price level is 0.05 and medium one is 0.043. For another asset currently priced at 19354, the next and previous major price levels are 20000 and 10000 respectively, and the next/previous medium levels are 20000 and 19000, and the next/previous weak levels are 19400 and 19300.
IMPORTANT: Please enable "Scale price chart only" in the chart's scale's options, as otherwise major levels may make the chart's scale very small and hard to read.
How it works
At any time, there are 3 levels of strength (1 leftmost digit, 2 leftmost digits, 3 leftmost digits) represented by different sizes, and 3 directional levels for each of these strengths (level above, level below, and half-level) represented by different colors and positions, around current price.
Indeed, contrary to other similar price levels scripts, we do not plot ALL price levels at all times, because otherwise the chart becomes wayyy too cluttered, and also it's highly processing intensive to plot so many lines. So we here use a dynamical approach: we plot only the relevant levels, the closest ones according to current price.
Hence, when a level disappears, it does not mean that it does not exist anymore, but simply that we are not drawing it right now because it is not pertinent for the current price movement (ie, too far away).
Breakouts can be detected in two different ways depending on if SMA is set to a value higher than 1 or not: if SMA == 1, then there is no smoothing, so the levels adapt instantaneously to the current price, so to detect breakout, you should refer to the levels at the previous tick and whether they were broken by current tick's price; if SMA > 1, then there is some smoothing, and so the levels will stay in-place even if there is a breakout, so it's easier to spot breakouts without having to look at the previous ticks, but on the other hand you won't see the new levels for the new price range until after a few more ticks for the smoothing window to adapt. Hence, by default, smoothing is disabled, so that you can see the currently pertinent levels at all time, even right after or during a breakout.
By default, the strong above level is in green, strong below level is in red, medium above level is in blue, medium below level is in yellow, and weak levels aren't displayed but can be. Half levels are also displayed, in a darker color. Strong levels are increments of the first leftmost digit (eg, 10000 to 20000), medium levels are increments of the second leftmost digit (eg, 19000 to 20000), and weak levels of the third leftmost digit (eg, 19100 to 19200). Instead of plotting all the psychological levels all at once as a grid, which makes the chart unintelligible, here the levels adapt dynamically around the current price, so that they show the above/below/half levels relatively to the current price.
Indeed, "half-levels" are also displayed (eg, medium level can also display 19500 instead of only 19000 or 20000). This was made because otherwise the gap between two levels was too big, especially for the strongest levels (eg, there was no major level between 20000 and 30000, but with a half-step we also get a half-level at 25000, and empirically price tends to respect these half levels - I also tried quarter levels but empirically the results were not good). In addition to this hard-coded half-level, you can also create more subdivisions (eg, quarter levels) by setting the simple moving average to a value higher than 1.
The script can be made to run on the daily timeframe whatever the current chart's timeframe is, to reduce the variability in levels, to make it less noisy than intraday price movement. But by default, the chart resolution is used, because I empirically found that the levels found with this indicator work on all time resolutions quite well.
The step can be adjusted to increase the gap between levels, eg, if you want to display one every 2 levels then input step = 2 (eg, 22000, 24000, 26000, etc), or if you want to display quarter levels, input 0.25 (eg, 22000, 22250, 22500, etc). The default values should fit most use cases and cover most psychological levels.
How to read
Focust first on bigger dotted levels, they are stronger and more likely to cause a rebound or a major event or price to stay at this level.
Remember that it's not enough to just look at levels, the context is important, because levels have various effects depending on current price movement: if price is above a level, the level is a support on which price can rebound; if price is below a level, the level is a resistance on which price can rebound (or break); and finally sometimes price also stays hovering around a level for some time.
Levels closer to 9 are less weaker, and levels closer to 0 are stronger, according to Zipf law. This is now reflected since v3 in the transparency, levels that are closer to 9 will be more transparent.
The switch in color for the same level illustrates how a level switches from being a support to a resistance and inversely. Eg, if a major level turns from green to red, then it changed from being a resistance (above) to a support (below).
As is well known in trading, longer standing levels are stronger. This indicator provides a direct illustration: in practice, the number of consecutive dots on the same line influences the strength of the level: the longer the chain of dots, the more you can expect this price level to be significant. The length does not mean the level will necessarily hold, but that other traders are likely to monitor if it holds, and if not then price will break down. Hence, longer levels are good spots to place stop losses, or to enter trades depending on your strategy. In general, a single dot is not enough to consider a level significant, but 2 or more is a good enough level, and 10+ is a strong level. Intuitively, this makes sense, and is what pro traders do: the longer a level is tested, the stronger it is. This indicator can visually represent this intuition and allows to use it as a more systematic trading signal.
Motivation
I initially made the first version of the PsychoLevels indicator mainly to train with PineScript, but I found it surprisingly accurate to define levels that are respected by price movements. So I guess it can be useful for new traders and experienced traders alike, as it's easy to forget that psychological levels can often be as strong if not stronger than technical levels. It can also be used to quickly screen other minor assets for trading opportunities. For example, a hybrid strategy would be to manually define levels on BTCUSD but using this script to automatically define levels in crypto altcoins and quickly screen them for a trade opportunity that can be greater than with BTCUSD but with the same trend.
Personally, although initially I did not believe an automated tool would work well for this purpose, I could now empirically verify that it is quite reliable for the purpose of detecting levels, and so I use it all the time to find the levels automatically and help me monitor them like a hawk, so that I only have to draw uber major levels, the ones that last between cycles and that are hard to autodetect, but otherwise all daily/weekly levels are usually covered. However, trendlines must still be drawn manually or with another indicator (but note that up to now I have found none that worked well enough), as PsychoLevels only draws levels (ie, horizontal lines, not oblique ones!).
Differences with the previous version PsychoLevels v2
price levels now have a transparency according to their importance for the human brain: numbers closer to 9 are weaker, and numbers closer to 0 are stronger and represent a major psychological threshold (eg, that's why prices marked as $9.99 sell better than $10.00). This option can be disabled to get the exact same behavior as v2.
modularized and typed code
PsychoLevels v2 can be found here:
Oscillator Workbench — Chart [LucF]█ OVERVIEW
This indicator uses an on-chart visual framework to help traders with the interpretation of any oscillator's behavior. The advantage of using this tool is that you do not need to know all the ins and outs of a particular oscillator such as RSI, CCI, Stochastic, etc. Your choice of oscillator and settings in this indicator will change its visuals, which allows you to evaluate different configurations in the context of how the workbench models oscillator behavior. My hope is that by using the workbench, you may come up with an oscillator selection and settings that produce visual cues you find useful in your trading.
The workbench works on any symbol and timeframe. It uses the same presentation engine as my Delta Volume Channels indicator; those already familiar with it will feel right at home here.
█ CONCEPTS
Oscillators
An oscillator is any signal that moves up and down a centerline. The centerline value is often zero or 50. Because the range of oscillator values is different than that of the symbol prices we look at on our charts, it is usually impossible to display an oscillator on the chart, so we typically put oscillators in a separate pane where they live in their own space. Each oscillator has its own profile and properties that dictate its behavior and interpretation. Oscillators can be bounded , meaning their values oscillate between fixed values such as 0 to 100 or +1 to -1, or unbounded when their maximum and minimum values are undefined.
Oscillator weight
How do you display an oscillator's value on a chart showing prices when both values are not on the same scale? The method I use here converts the oscillator's value into a percentage that is used to weigh a reference line. The weight of the oscillator is calculated by maintaining its highest and lowest value above and below its centerline since the beginning of the chart's history. The oscillator's relative position in either of those spaces is then converted to a percentage, yielding a positive or negative value depending on whether the oscillator is above or below its centerline. This method works equally well with bounded and unbounded oscillators.
Oscillator Channel
The oscillator channel is the space between two moving averages: the reference line and a weighted version of that line. The reference line is a moving average of a type, source and length which you select. The weighted line uses the same settings, but it averages the oscillator-weighted price source.
The weight applied to the source of the reference line can also include the relative size of the bar's volume in relation to previous bars. The effect of this is that the oscillator's weight on bars with higher total volume will carry greater weight than those with lesser volume.
The oscillator channel can be in one of four states, each having its corresponding color:
• Bull (teal): The weighted line is above the reference line.
• Strong bull (lime): The bull condition is fulfilled and the bar's close is above the reference line and both the reference and the weighted lines are rising.
• Bear (maroon): The weighted line is below the reference line.
• Strong bear (pink): The bear condition is fulfilled and the bar's close is below the reference line and both the reference and the weighted lines are falling.
Divergences
In the context of this indicator, a divergence is any bar where the slope of the reference line does not match that of the weighted line. No directional bias is assigned to divergences when they occur. You can also choose to define divergences as differences in polarity between the oscillator's slope and the polarity of close-to-close values. This indicator's divergences are designed to identify transition levels. They have no polarity; their bullish/bearish bias is determined by the behavior of price relative to the divergence channel after the divergence channel is built.
Divergence Channel
The divergence channel is the space between two levels (by default, the bar's low and high ) saved when divergences occur. When price has breached a channel and a new divergence occurs, a new channel is created. Until that new channel is breached, bars where additional divergences occur will expand the channel's levels if the bar's price points are outside the channel.
Price breaches of the divergence channel will change its state. Divergence channels can be in one of five different states:
• Bull (teal): Price has breached the channel to the upside.
• Strong bull (lime): The bull condition is fulfilled and the oscillator channel is in the strong bull state.
• Bear (maroon): Price has breached the channel to the downside.
• Strong bear (pink): The bear condition is fulfilled and the oscillator channel is in the strong bear state.
• Neutral (gray): The channel has not been breached.
█ HOW TO USE THE INDICATOR
Load the indicator on an active chart (see here if you don't know how).
The default configuration displays:
• The Divergence channel's levels.
• Bar colors using the state of the oscillator channel.
The default settings use:
• RSI as the oscillator, using the close source and a length of 20 bars.
• An Arnaud-Legoux moving average on the close and a length of 20 bars as the reference line.
• The weighted version of the reference line uses only the oscillator's weight, i.e., without the relative volume's weight.
The weighted line is capped to three standard deviations of the reference.
• The divergence channel's levels are determined using the high and low of the bars where divergences occur.
Breaches of the channel require a bar's low to move above the top of the channel, and the bar's high to move below the channel's bottom.
No markers appear on the chart; if you want to create alerts from this script, you will need first to define the conditions that will trigger the markers, then create the alert, which will trigger on those same conditions.
To learn more about how to use this indicator, you must understand the concepts it uses and the information it displays, which requires reading this description. There are no videos to explain it.
█ FEATURES
The script's inputs are divided in five sections: "Oscillator", "Oscillator channel", "Divergence channel", "Bar Coloring" and "Marker/Alert Conditions".
Oscillator
This is where you configure the oscillator you want to study. Thirty oscillators are available to choose from, but you can also use an oscillator from another indicator that is on your chart, if you want. When you select an external indicator's plot as the oscillator, you must also specify the value of its centerline.
Oscillator Channel
Here, you control the visibility and colors of the reference line, its weighted version, and the oscillator channel between them.
You also specify what type of moving average you want to use as a reference line, its source and its length. This acts as the oscillator channel's baseline. The weighted line is also a moving average of the same type and length as the reference line, except that it will be calculated from the weighted version of the source used in the reference line. By default, the weighted line is capped to three standard deviations of the reference line. You can change that value, and also elect to cap using a multiple of ATR instead. The cap provides a mechanism to control how far the weighted line swings from the reference line. This section is also where you can enable the relative volume component of the weight.
Divergence Channel
This is where you control the appearance of the divergence channel and the key price values used in determining the channel's levels and breaching conditions. These choices have an impact on the behavior of the channel. More generous level prices like the default low and high selection will produce more conservative channels, as will the default choice for breach prices.
In this section, you can also enable a mode where an attempt is made to estimate the channel's bias before price breaches the channel. When it is enabled, successive increases/decreases of the channel's top and bottom levels are counted as new divergences occur. When one count is greater than the other, a bull/bear bias is inferred from it. You can also change the detection mode of divergences, and choose to display a mark above or below bars where divergences occur.
Bar Coloring
You specify here:
• The method used to color chart bars, if you choose to do so.
• If you want to hollow out the bodies of bars where volume has not increased since the last bar.
Marker/Alert Conditions
Here, you specify the conditions that will trigger up or down markers. The trigger conditions can include a combination of state transitions of the oscillator and the divergence channels. The triggering conditions can be filtered using a variety of conditions.
Configuring the marker conditions is necessary before creating an alert from this script, as the alert will use the marker conditions to trigger.
Realtime values will repaint, as is usually the case with oscillators, but markers only appear on bar closes, so they will not repaint. Keep in mind, when looking at markers on historical bars, that they are positioned on the bar when it closes — NOT when it opens.
Raw values
The raw values calculated by this script can be inspected using the Data Window, including the oscillator's value and the weights.
█ INTERPRETATION
Except when mentioned otherwise, this section's charts use the indicator's default settings, with different visual components turned on or off.
The aim of the oscillator channel is to provide a visual representation of an oscillator's general behavior. The simplest characteristic of the channel is its bull/bear state, determined by whether the weighted line is above or below the reference line. One can then distinguish between its bull and strong bull states, as transitions from strong bull to bull states will generally happen when trends are losing steam. While one should not infer a reversal from such transitions, they can be a good place to tighten stops. Only time will tell if a reversal will occur. One or more divergences will often occur before reversals. This shows the oscillator channel, with the reference line and the thicker, weighted line:
The nature of the divergence channel 's design makes it particularly adept at identifying consolidation areas if its settings are kept on the conservative side. The divergence channel will also reveal transition areas. A gray divergence channel should usually be considered a no-trade zone. More adventurous traders can use the oscillator channel to orient their trade entries if they accept the risk of trading in a neutral divergence channel, which by definition will not have been breached by price. This show only the divergence channels:
This chart shows divergence channels and their levels, and colors bars on divergences and on the state of the oscillator channel, which is not visible on the chart:
If your charts are already busy with other stuff you want to hold on to, you could consider using only the chart bar coloring component of this indicator. Here we only color bars using the combined state of the oscillator and divergence channel, and we do not color the bodies of bars where volume has not increased. Note that my chart's settings do not color the candle bodies:
At its simplest, one way to use this indicator would be to look for overlaps of the strong bull/bear colors in both the oscillator channel and a divergence channel, as these identify points where price is breaching the divergence channel when the oscillator's state is consistent with the direction of the breach.
Tip
One way to use the Workbench is to combine it with my Delta Volume Channels indicator. If both indicators use the same MA as a reference line, you can display its delta volume channel instead of the oscillator channel.
This chart shows such a setup. The Workbench displays its divergence levels, the weighted reference line using the default RSI oscillator, and colors bars on divergences. The DV Channels indicator only displays its delta volume channel, which uses the same MA as the workbench for its baseline. This way you can ascertain the volume delta situation in contrast with the visuals of the Workbench:
█ LIMITATIONS
• For some of the oscillators, assumptions are made concerning their different parameters when they are more complex than just a source and length.
See the `oscCalc()` function in this indicator's code for all the details, and ask me in a comment if you can't find the information you need.
• When an oscillator using volume is selected and no volume information is available for the chart's symbol, an error will occur.
• The method I use to convert an oscillator's value into a percentage is fragile in the early history of datasets
because of the nascent expression of the oscillator's range during those early bars.
█ NOTES
Working with this workbench
This indicator is called a workbench for a reason; it is designed for traders interested in exploring its behavior with different oscillators and settings, in the hope they can come up with a setup that suits their trading methodology. I cannot tell you which setup is the best because its setup should be compatible with your trading methodology, which may require faster or slower transitions, thus different configurations of the settings affecting the calculations of the divergence channels.
For Pine Script™ Coders
• This script uses the new overload of the fill() function which now makes it possible to do vertical gradients in Pine. I use it for both channels displayed by this script.
• I use the new arguments for plot() 's `display` parameter to control where the script plots some of its values,
namely those I only want to appear in the script's status line and in the Data Window.
• I used my ta library for some of the oscillator calculations and helper functions.
• I also used TradingView's ta library for other oscillator calculations.
• I wrote my script using the revised recommendations in the Style Guide from the Pine v5 User Manual.
Position Tool█ OVERVIEW
This script is an interactive measurement tool that can be used to evaluate or keep track of trades. Like the long and short position drawing tools, it calculates a risk reward ratio and a risk-adjusted position size from the entry, stop and take profit levels, but it also does much more:
• It can be used to configure long or short trades.
• All monetary values can be expressed in any number of currencies.
• The value of tick/pip movement (which varies with the position's size) is displayed in the currency you have selected.
• The CAGR ( Compound Annual Growth Rate ) for the trade can be displayed.
• It does live tracking of the position.
• You can configure alerts on entries and exits.
█ HOW TO USE IT
Load the indicator on an active chart (see here if you don't know how).
When you first load this script on a chart, you will enter an interactive selection mode where the script asks you to pick three points in price and time on your chart by clicking on the chart. Directions will appear in a blue box at the bottom of the screen with each click of the mouse. The first selection is the entry point for the trade you are considering, which takes into account both the time and level you choose, the next are the take profit and stop levels. Once you have selected all three points, the script will draw trade zones and labels containing the trade metrics. The script determines if the trade is a long or short from the position of the take profit and stop loss levels in relation to the entry price. If the take profit level is above the entry price, the stop must be below and vice versa, otherwise an error occurs.
You can change levels by dragging the handles that appear when you select the indicator, or by entering new values in the script's settings. The only way to re-enter interactive mode is to re-add the indicator to your chart.
Once you place the position tool on a chart, it will appear at the same levels on all symbols you use. If your scale is not set to "Scale price chart only", the position tool's levels will be taken into account when scaling the chart, which can cause the symbol's bars to be compressed. If your scale is set to "Scale price chart only", the position tool will still be there, but it will not impact the scale of the chart's bars, so you won't see it if it sits outside the symbol's price scale.
If you select the position tool on your chart and delete it, this will also delete the indicator from the chart. You will need to re-add it if you want to draw another position tool. You can add multiple instances of the indicator if you need a position tool on more than one of your charts.
█ FEATURES
Display
The position tool displays the following information for entries:
• The entry's price level with an '@' sign before it.
• Open or Closed P&L : For an open trade, the "Open P&L" displays the difference in money value between the entry level and the chart's current price.
For a closed trade, the "Closed P&L" displays the realized P&L on the trade.
• Quantity : The trade size, which takes into account the risk tolerance you set in the script's settings.
• RR : The reward to risk ratio expresses the relationship of the distance between the entry and the take profit level vs the entry and the stop level.
Example: A $100 stop with a $100 target will have a ratio of 1:1, whereas a $200 target with the same stop will have a 2:1 ratio.
• Per tick/pip : Represents the money value of a tick or pip movement.
• CAGR : The Compound Annual Growth Rate will be displayed on the main order label on trades that exceed one day in duration.
This value is calculated the same way as in our CAGR Custom Range indicator.
If the trade duration is less than one day, the metric will not be present in the display.
The stop and take profit levels display:
• Their price level with an '@' sign before it.
• Their distance from the entry in money value, percentage and ticks/pips.
• The projected end money value of the position if the level is reached. These values are calculated based on the trade size and the currency.
Currency adjustments
This indicator modifies the trade label's colors and values based on the final Profit and Loss (P&L), which considers the dynamic exchange rate between base and conversion currencies in its calculations when the conversion currency is a specified value other than the default. Depending on the cross rate between the base and account currencies, this process can yield a negative P&L on an otherwise successful simulated trade.
For instance, if your account is in currency XYZ, you might buy 10 Apple shares at $150 each, with the XYZ to USD exchange rate being 2:1. This purchase would cost you 3000 units of XYZ. Suppose that later on, the shares appreciate to $170 each, and you decide to sell. One might expect this trade to result in profit. However, if the exchange rate has now equalized to 1:1, the return on selling the shares, calculated in XYZ, would only be 1700 units, resulting in a loss of 1300 units XYZ.
The indicator will mark the P&L and the target labels in red in such cases, regardless of whether the market price reached the profit target, as the trade produced a net loss due to reduced funds after currency conversion. Conversely, an otherwise unsuccessful position can result in a net profit in the account currency due to conversion rate fluctuations. The final losses or gains appear in the label metrics, and the corresponding color coding reflects the trade's success or failure.
Settings
The settings in the "Trade sizing" section are used to calculate the position size and the monetary value of trades. Two types of risk can be chosen from the menu; a percentage based risk calculation, or a fixed money value. The risk is used to calculate the quantity of units to purchase to achieve that level of risk exposure. Example: An account size of $1000 and 10% risk will have a projected end amount of $900 if the stop loss is hit. The quantity is a product of this relationship; a projected number of units to allow for the equivalent of $100 of risk exposure over the change in price from the entry to the stop value.
The "Trade levels" allow you to manually set the entry, take profit and stop levels of an existing position tool on your chart.
You can control the appearance of the tool and the values it displays in the settings following these first two sections.
Alerts
Three alerts that will trigger when you configure an alert on this indicator. The first will send an alert when the entry price is breached by price action if that price has not already been breached in the previous price history. This is dependant on the entry location you select when placing the indicator on the chart. The other two alerts will trigger when either the stop loss or the take profit level is breached to signal that a trade exit has occurred.
█ NOTES FOR Pine Script™ CODERS
• Interactive inputs are implemented for input.time() and input.price() . These specialized input functions allow users to interact with a script.
You can create one interactive input for both time and price values by using the same `inline` argument in a pair of input.time() and input.price() function calls.
• We use the `cagr()` function from our ta library.
• The script uses the runtime.error() function to throw an error if the stop and limit prices are not placed on opposing sides of the entry price.
• We use the `currency` parameter in a request.security() call to convert currencies.
Look first. Then leap.
Ichimoku Cloud MasterIchimoku Cloud Master aims to provide the ichimoku trader with easy alert functionality to not miss out on valuable trade setups. The key purpose of this script is to better visualise crucial moments in Ichimoku trading. These alerts should not be used for botting in my opinion as they always need a human to confirm the ichimoku market structure. For example, is the Kijun-Sen flat and too far away from price? A good ichimoku trader will not enter at such a point in time.
Explanation of script:
Chikou(lagging span): pink line, this is price plotted 26 bars ago. People ignore the power of this it is crucial to see how chikou behaves towards past price action as seen in the chart below where we got an entry at red arrow because chikou bounced from past fractal bottom.
Kijun-Sen(base line): Black line or color coded line. This is the equilibrium of last 26 candles. To me this is the most important line in the system as it attracts price.
Kijun = (Highest high of 26 periods + Lowest low of 26 periods) ÷ 2
Tenkan-Sen(conversion line): Blue line. This is the equilibrium of last 9 candles. In a strong uptrend price stays above this line.
Tenkan = (Highest high of 9 periods + Lowest low of 9 periods) ÷ 2
Senkou A (Leading span A)= Pink cloud line, this is the average of the 2 components projected 26 bars in the future.
Senkou A = (Tenkan + Kijun) ÷ 2
Senkou B (Leading span B) = Green cloud line, this is the 52 day equilibrium projected 26 bars in the future.
Senkou B = (Highest high of prior 52 periods + Lowest low of prior 52 periods) ÷ 2
Notice how the distance between Chikou and the cloud is also 52 bars. This is all part of Hosoda's numbers which I am not going to explain here.
Fractals: These are the black triangles you find at key turning point. If you want to know how they work reseach williams fractals. I've used fractals with a period of 9 as it is an ichimoku number. These fractals are useful when working with ichimoku wave theory. Again I will not explain that here but in further education
Fractal Support: Ability to extend lines from the fractals which can be used as an entry/exit mechanism in your trading. For example wait for tenkan to cross kijun and then enter on fractal breakout.
Signals:
Crossing of Chikou (lagging span) with past Kijun-Sen: this will color code the Bars / Kijun-Sen (you can turn this off in options)
The script also has a signal for this, this will be the green and purple diamonds. Where green is bullish and purple is bearish.
wy is this important?
When current price plotted 26 candles back (chikou) crosses over the past equilibrium (kijun-sen) this usualy means price has moved past resistance levels where sellers come in. This indicates a switch in market structure and price is bullish from this point, this is the same in the other direction.
Kumo Twist: when the kumo cloud (future) has a crossover from for example green to red (bull to bear). The script plots these using the colored cross symbols as seen in the picture above. A chikou cross + a Kumo twist at same bar of next to eachother below the cloud can be a great entry sign: this would be an entry after cross in the chart above.
Kijun Bounce: when in an uptrend the price retraces back to Kijun-Sen and starts to go back up. These are marked by the yellow circles as seen in chart below:
low below Kijun-Sen and close above it
Strong Trend: when Tenkan is above Kijun, price above cloud, future cloud green, chikou above close, chikou above Kijun we establish a strong bullish trend. For bearish the exact opposite. The script has a function to send an alert at the start of such trends and to plot them with small colored circles above the bars.
Customisation:
I've added options to disable specific aspects of the indicator for those traders who do not want to use all aspects of the indicator. In the customisation tab I've given each part a clear title so you can use your own colors/shapes.
The perfect entry?
Further info:
Look into my education pane, I will be adding education in the future. The chance of me making a more advanced version of the script including line forecasting etc is rather high so watch out for that.
For those who want to master this system I recommend reading the book:
How to make money with the ichimoku system by Balkrishna M. Sadekar
Or the originals books by Hosoda the inventor of Ichimoku if you can get your hands on them and can read Japanese.
Almost all info about the ichimoku system you find on the internet will lose you money because they reduce the system to simple signals that do not generate money.
I will be providing educational material on tradingview using this indicator.
Coin Bureau BB/EMA/RSI IndicatorThis indicator was inspired by Coin Bureau's How To Spot The Crypto Top video. In the video, Coin Bureau uses Bollinger bands, 7-period EMA and RSI to look for early signs of a top, thus presenting an opportunity to sell.
Using the basic principles found in the video, I've made a tentative indicator as a way to visualise all 3 indicators at once. Alerts will only fire when all 3 criteria are met:
Price closes outside 20-period Bollinger bands
Price closes ~2sd away from 7-period EMA
RSI is overbought or oversold
The indicator will also update in real-time and show when 1, 2 or all 3 conditions are satisfied. Additionally, there is built-in functionality to toggle historical/current alerts and users can set their own bounds for what constitutes a buy or sell alert.
This is just a personal project purely for edutainment purposes and should not be used to make financial decisions. This project is not affiliated with Coin Bureau.
Some caveats:
Using only 7 periods to calculate the standard deviation of price data will not lead to a statistically significant result, thus this figure may have no right being in the script. However, this was more to trial some techniques and to get acquainted with the pine scripting language.
As you can see, there are a lot of false positives. There are moments when the indicator flashes a sell alert only for the price to keep on rising. This is due to the specificity/sensitivity trade-off. The indicator has been tuned to give the optimal sensitivity (the more critical component). These are the best results I could find for this asset in this time frame.
3rd WaveHello All,
In Elliott Wave Theory, 3rd wave is not the shortest one in the waves 1/3/5 and it's usually longest one. so if we can catch it then we may get good opportunities to trade. This script finds 3rd wave experimentally. it can be also the 3rd waves in the waves 1, 3, 5, A and C. the 3rd wave should have greater volume than other waves, the script can check its volume and compare with the volumes of the waves 1 and 2 optionally.
Pine Team released Pine version 5! This script was developed in v5 and it uses Library feature of Pine v5 for the zigzag functions. This script is also an example for the Pine developers who learn Pine v5 and Libraries.
Options:
Zigzag Period: is the length that is used to calculate highest/lowest and the zigzag waves
Min/Max Retracements: is the retracement rates to check the wave 2 according to wave 1. for example; if min/max values are 0.500-0.618 then wave 2 must be minimum 0.500 of wave 1 and maximum 0.618 of wave 1.
Check Volume Support: is an option to compare the volumes of1. 2. and . waves. if you enable this option then the script checks their volume and 3rd wave volume must be greater then 1 and 2
there are 4 options for the targets. you can enable/disable and change their levels. targets are calculated using length of wave 1.
Options to show breakout zone, zigzag, wave 1 and 2.
and some options for the colors.
The Library that is used in this script:
P.S. This is an experimental work and can be improved. So do not hesitate to drop your comments under the script ;)
Enjoy!
[SCL] Significant Figures Example FunctionThis script consist of a single example function that takes a floating-point number - one that can, but doesn't have to, include a decimal point - and converts it to a floating-point number with only a certain number of significant digits left.
I'm not aware of another script that does this. There might well be a simpler way, in which case please do let me know.
For example, say you want to display a variable from your script to the user and it comes out to something like 45.366666666666666666666667 or whatever. That looks awful when you, for example, print it in a label.
Now, you could round it up to the nearest integer easily using a built-in function, or even to a certain number of decimal places using a reasonably simple custom function.
But that's a bit arbitrary. Suppose you don't know what asset the script will be used on, and so you can't predict what the price is, and what the value will turn out to be.
It could be 0.00045366666666666666666666667 instead. Now if you round it up to 3 decimal places it comes out as 0.000, which is useless.
My function will round that number to 0.0004536 instead, if told to do it to 4 significant digits.
You're free to use this function in your own scripts, including closed-source scripts, without asking permission. Credit to @SimpleCryptoLife would be appreciated.
Filter Information Box - PineCoders FAQWhen designing filters it can be interesting to have information about their characteristics, which can be obtained from the set of filter coefficients (weights). The following script analyzes the impulse response of a filter in order to return the following information:
Lag
Smoothness via the Herfindahl index
Percentage Overshoot
Percentage Of Positive Weights
The script also attempts to determine the type of the analyzed filter, and will issue warnings when the filter shows signs of unwanted behavior.
DISPLAYED INFORMATION AND METHODS
The script displays one box on the chart containing two sections. The filter metrics section displays the following information:
- Lag : Measured in bars and calculated from the convolution between the filter's impulse response and a linearly increasing sequence of value 0,1,2,3... . This sequence resets when the impulse response crosses under/over 0.
- Herfindahl index : A measure of the filter's smoothness described by Valeriy Zakamulin. The Herfindahl index measures the concentration of the filter weights by summing the squared filter weights, with lower values suggesting a smoother filter. With normalized weights the minimum value of the Herfindahl index for low-pass filters is 1/N where N is the filter length.
- Percentage Overshoot : Defined as the maximum value of the filter step response, minus 1 multiplied by 100. Larger values suggest higher overshoots.
- Percentage Positive Weights : Percentage of filter weights greater than 0.
Each of these calculations is based on the filter's impulse response, with the impulse position controlled by the Impulse Position setting (its default is 1000). Make sure the number of inputs the filter uses is smaller than Impulse Position and that the number of bars on the chart is also greater than Impulse Position . In order for these metrics to be as accurate as possible, make sure the filter weights add up to 1 for low-pass and band-stop filters, and 0 for high-pass and band-pass filters.
The comments section displays information related to the type of filter analyzed. The detection algorithm is based on the metrics described above. The script can detect the following type of filters:
All-Pass
Low-Pass
High-Pass
Band-Pass
Band-Stop
It is assumed that the user is analyzing one of these types of filters. The comments box also displays various warnings. For example, a warning will be displayed when a low-pass/band-stop filter has a non-unity pass-band, and another is displayed if the filter overshoot is considered too important.
HOW TO SET THE SCRIPT UP
In order to use this script, the user must first enter the filter settings in the section provided for this purpose in the top section of the script. The filter to be analyzed must then be entered into the:
f(input)
function, where `input` is the filter's input source. By default, this function is a simple moving average of period length . Be sure to remove it.
If, for example, we wanted to analyze a Blackman filter, we would enter the following:
f(input)=>
pi = 3.14159,sum = 0.,sumw = 0.
for i = 0 to length-1
k = i/length
w = 0.42 - 0.5 * cos(2 * pi * k) + 0.08 * cos(4 * pi * k)
sumw := sumw + w
sum := sum + w*input
sum/sumw
EXAMPLES
In this section we will look at the information given by the script using various filters. The first filter we will showcase is the linearly weighted moving average (WMA) of period 9.
As we can see, its lag is 2.6667, which is indeed correct as the closed form of the lag of the WMA is equal to (period-1)/3 , which for period 9 gives (9-1)/3 which is approximately equal to 2.6667. The WMA does not have overshoots, this is shown by the the percentage overshoot value being equal to 0%. Finally, the percentage of positive weights is 100%, as the WMA does not possess negative weights.
Lets now analyze the Hull moving average of period 9. This moving average aims to provide a low-lag response.
Here we can see how the lag is way lower than that of the WMA. We can also see that the Herfindahl index is higher which indicates the WMA is smoother than the HMA. In order to reduce lag the HMA use negative weights, here 55% (as there are 45% of positive ones). The use of negative weights creates overshoots, we can see with the percentage overshoot being 26.6667%.
The WMA and HMA are both low-pass filters. In both cases the script correctly detected this information. Let's now analyze a simple high-pass filter, calculated as follows:
input - sma(input,length)
Most weights of a high-pass filters are negative, which is why the lag value is negative. This would suggest the indicator is able to predict future input values, which of course is not possible. In the case of high-pass filters, the Herfindahl index is greater than 0.5 and converges toward 1, with higher values of length . The comment box correctly detected the type of filter we were using.
Let's now test the script using the simple center of gravity bandpass filter calculated as follows:
wma(input,length) - sma(input,length)
The script correctly detected the type of filter we are using. Another type of filter that the script can detect is band-stop filters. A simple band-stop filter can be made as follows:
input - (wma(input,length) - sma(input,length))
The script correctly detect the type of filter. Like high-pass filters the Herfindahl index is greater than 0.5 and converges toward 1, with greater values of length . Finally the script can detect all-pass filters, which are filters that do not change the frequency content of the input.
WARNING COMMENTS
The script can give warning when certain filter characteristics are detected. One of them is non-unity pass-band for low-pass filters. This warning comment is displayed when the weights of the filter do not add up to 1. As an example, let's use the following function as a filter:
sum(input,length)
Here the filter pass-band has non unity, and the sum of the weights is equal to length . Therefore the script would display the following comments:
We can also see how the metrics go wild (note that no filter type is detected, as the detected filter could be of the wrong type). The comment mentioning the detection of high overshoot appears when the percentage overshoot is greater than 50%. For example if we use the following filter:
5*wma(input,length) - 4*sma(input,length)
The script would display the following comment:
We can indeed see high overshoots from the filter:
@alexgrover for PineCoders
Look first. Then leap.
TTM Squeeze Scanner This script scans for TTM Squeezes for the crypto symbols included in the body of the script. The timeframe for the squeeze scan is controlled within the input not the chart.
This script is a merge of @Nico.Muselle's TTM Squeeze script and @QuantNomad's custom screener script. Thanks to both of them!
RSI ADX Bollinger Analysis High-level purpose and design philosophy
This indicator — RSI-ADX-Bollinger Analysis — is a compact, educational market-analysis toolkit that blends momentum (RSI), trend strength (ADX), volatility structure (Bollinger Bands) and simple volumetrics to provide traders a snapshot of market condition and trade idea quality. The design philosophy is explicit and layered: use each component to answer a different question about price action (momentum, conviction, volatility, participation), then combine answers to form a more robust, explainable signal. The mashup is intended for analysis and learning, not automatic execution: it surfaces the why behind signals so traders can test, learn and apply rules with risk management.
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What each indicator contributes (component-by-component)
RSI (Relative Strength Index) — role and behavior: RSI measures short-term momentum by comparing recent gains to recent losses. A high RSI (near or above the overbought threshold) indicates strong recent buying pressure and potential exhaustion if price is extended. A low RSI (near or below the oversold threshold) indicates strong recent selling pressure and potential exhaustion or a value area for mean-reversion. In this dashboard RSI is used as the primary momentum trigger: it helps identify whether price is locally over-extended on the buy or sell side.
ADX (Average Directional Index) — role and behavior: ADX measures trend strength independently of direction. When ADX rises above a chosen threshold (e.g., 25), it signals that the market is trending with conviction; ADX below the threshold suggests range or weak trend. Because patterns and momentum signals perform differently in trending vs. ranging markets, ADX is used here as a filter: only when ADX indicates sufficient directional strength does the system treat RSI+BB breakouts as meaningful trade candidates.
Bollinger Bands — role and behavior: Bollinger Bands (20-period basis ± N standard deviations) show volatility envelope and relative price position vs. a volatility-adjusted mean. Price outside the upper band suggests pronounced extension relative to recent volatility; price outside the lower band suggests extended weakness. A band expansion (increasing width) signals volatility breakout potential; contraction signals range-bound conditions and potential squeeze. In this dashboard, Bollinger Bands provide the volatility/structural context: RSI extremes plus price beyond the band imply a stronger, volatility-backed move.
Volume split & basic MA trend — role and behavior: Buy-like and sell-like volume (simple heuristic using close>open or closeopen) or sell-like (close1.2 for validation and compare win rate and expectancy.
4. TF alignment: Accept signals only when higher timeframe (e.g., 4h) trend agrees — compare results.
5. Parameter sensitivity: Vary RSI threshold (70/30 vs 80/20), Bollinger stddev (2 vs 2.5), and ADX threshold (25 vs 30) and measure stability of results.
These exercises teach both statistical thinking and the specific failure modes of the mashup.
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Limitations, failure modes and caveats (explicit & teachable)
• ADX and Bollinger measures lag during fast-moving news events — signals can be late or wrong during earnings, macro shocks, or illiquid sessions.
• Volume classification by open/close is a heuristic; it does not equal TAPEDATA, footprint or signed volume. Use it as supportive evidence, not definitive proof.
• RSI can remain overbought or oversold for extended stretches in persistent trends — relying solely on RSI extremes without ADX or BB context invites large drawdowns.
• Small-cap or low-liquidity instruments yield noisy band behavior and unreliable volume ratios.
Being explicit about these limitations is a strong point in a TradingView description — it demonstrates transparency and educational intent.
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Originality & mashup justification (text you can paste)
This script intentionally combines classical momentum (RSI), volatility envelope (Bollinger Bands) and trend-strength (ADX) because each indicator answers a different and complementary question: RSI answers is price locally extreme?, Bollinger answers is price outside normal volatility?, and ADX answers is the market moving with conviction?. Volume participation then acts as a practical check for real market involvement. This combination is not a simple “indicator mashup”; it is a designed ensemble where each element reduces the others’ failure modes and together produce a teachable, testable signal framework. The script’s purpose is educational and analytical — to show traders how to interpret the interplay of momentum, volatility, and trend strength.
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TradingView publication guidance & compliance checklist
To satisfy TradingView rules about mashups and descriptions, include the following items in your script description (without exposing source code):
1. Purpose statement: One or two lines describing the script’s objective (educational multi-indicator market overview and idea filter).
2. Component list: Name the major modules (RSI, Bollinger Bands, ADX, volume heuristic, SMA trend checks, signal tracking) and one-sentence reason for each.
3. How they interact: A succinct non-code explanation: “RSI finds momentum extremes; Bollinger confirms volatility expansion; ADX confirms trend strength; all three must align for a BUY/SELL.”
4. Inputs: List adjustable inputs (RSI length and thresholds, BB length & stddev, ADX threshold & smoothing, volume MA, table position/size).
5. Usage instructions: Short workflow (check TF alignment → confirm participation → define stop & R:R → backtest).
6. Limitations & assumptions: Explicitly state volume is approximated, ADX has lag, and avoid promising guaranteed profits.
7. Non-promotional language: No external contact info, ads, claims of exclusivity or guaranteed outcomes.
8. Trademark clause: If you used trademark symbols, remove or provide registration proof.
9. Risk disclaimer: Add the copy-ready disclaimer below.
This matches TradingView’s request for meaningful descriptions that explain originality and inter-component reasoning.
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Copy-ready short publication description (paste into TradingView)
Advanced RSI-ADX-Bollinger Market Overview — educational multi-indicator dashboard. This script combines RSI (momentum extremes), Bollinger Bands (volatility envelope and band expansion), ADX (trend strength), simple SMA trend bias and a basic buy/sell volume heuristic to surface high-quality idea candidates. Signals require alignment of momentum, volatility expansion and rising ADX; volume participation is displayed to support signal confidence. Inputs are configurable (RSI length/levels, BB length/stddev, ADX length/threshold, volume MA, display options). This tool is intended for analysis and learning — not for automated execution. Users should back test and apply robust risk management. Limitations: volume classification here is a heuristic (close>open), ADX and BB measures lag in fast news events, and results vary by instrument liquidity.
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Copy-ready risk & misuse disclaimer (paste into description or help file)
This script is provided for educational and analytical purposes only and does not constitute financial or investment advice. It does not guarantee profits. Indicators are heuristics and may give false or late signals; always back test and paper-trade before using real capital. The author is not responsible for trading losses resulting from the use or misuse of this indicator. Use proper position sizing and risk controls.
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Risk Disclaimer: This tool is provided for education and analysis only. It is not financial advice and does not guarantee returns. Users assume all risk for trades made based on this script. Back test thoroughly and use proper risk management.
ACR(Average Candle Range) With TargetsWhat is ACR?
The Average Candle Range (ACR) is a custom volatility metric that calculates the mean distance between the high and low of a set number of past candles. ACR focuses only on the actual candle range (high - low) of specific past candles on a chosen timeframe.
This script calculates and visualizes the Average Candle Range (ACR) over a user-defined number of candles on a custom timeframe. It displays a table of recent range values, plots dynamic bullish and bearish target levels, and marks the start of each new candle with a vertical line. All calculations update in real time as price action develops. This script was inspired by the “ICT ADR Levels - Judas x Daily Range Meter°” by toodegrees.
Key Features
Custom Timeframe Selection: Choose any timeframe (e.g., 1D, 4H, 15m) for analysis.
User-Defined Lookback: Calculate the average range across 1 to 10 previous candles.
Dynamic Targets:
Bullish Target: Current candle low + ACR.
Bearish Target: Current candle high – ACR.
Live Updates: Targets adjust intrabar as highs or lows change during the current candle.
Candle Start Markers: Vertical lines denote the open of each new candle on the selected timeframe.
Floating Range Table:
Displays the current ACR value.
Lists individual ranges for the previous five candles.
Extend Target Lines: Choose to extend bullish and bearish target levels fully across the screen.
Global Visibility Controls: Toggle on/off all visual elements (targets, vertical lines, and table) for a cleaner view.
How It Works
At each new candle on the user-selected timeframe, the script:
Draws a vertical line at the candle’s open.
Recalculates the ACR based on the inputted previous number of candles.
Plots target levels using the current candle's developing high and low values.
Limitation
Once the price has already moved a full ACR in the opposite direction from your intended trade, the associated target loses its practical value. For example, if you intended to trade long but the bearish ACR target is hit first, the bullish target is no longer a reliable reference for that session.
Use Case
This tool is designed for traders who:
Want to visualize the average movement range of candles over time.
Use higher or lower timeframe candles as structural anchors.
Require real-time range-based price levels for intraday or swing decision-making.
This script does not generate entry or exit signals. Instead, it supports range awareness and target projection based on historical candle behavior.
Key Difference from Similar Tools
While this script was inspired by “ICT ADR Levels - Judas x Daily Range Meter°” by toodegrees, it introduces a major enhancement: the ability to customize the timeframe used for calculating the range. Most ADR or candle-range tools are locked to a single timeframe (e.g., daily), but this version gives traders full control over the analysis window. This makes it adaptable to a wide range of strategies, including intraday and swing trading, across any market or asset.
Ultimate JLines & MTF EMA (Configurable, Labels)## Ultimate JLines & MTF EMA (Configurable, Labels) — Script Overview
This Pine Script is a comprehensive, multi-timeframe indicator based on J Trader concepts. It overlays various Exponential Moving Averages (EMAs), VWAP, inside bar highlights, and dynamic labels onto price charts. The script is highly configurable, allowing users to tailor which elements are displayed and how they appear.
### Key Features
#### 1. **Multi-Timeframe JLines**
- **JLines** are pairs of EMAs (default lengths: 72 and 89) calculated on several timeframes:
- 1 minute (1m)
- 3 minutes (3m)
- 5 minutes (5m)
- 1 hour (1h)
- Custom timeframe (user-selectable)
- Each pair can be visualized as individual lines and as a "cloud" (shaded area between the two EMAs).
- Colors and opacity for each timeframe are user-configurable.
#### 2. **200 EMA on Multiple Timeframes**
- Plots the 200-period EMA on selectable timeframes: 1m, 3m, 5m, 15m, and 1h.
- Each can be toggled independently and colored as desired.
#### 3. **9 EMA and VWAP**
- Plots a 9-period EMA, either on the chart’s current timeframe or a user-specified one.
- Plots VWAP (Volume-Weighted Average Price) for additional trend context.
#### 4. **5/15 EMA Cross Cloud (5min)**
- Calculates and optionally displays a shaded "cloud" between the 5-period and 15-period EMAs on the 5-minute chart.
- Highlights bullish (5 EMA above 15 EMA) and bearish (5 EMA below 15 EMA) conditions with different colors.
- Optionally displays the 5 and 15 EMA lines themselves.
#### 5. **Inside Bar Highlighting**
- Highlights bars where the current high is less than or equal to the previous high and the low is greater than or equal to the previous low (inside bars).
- Color is user-configurable.
#### 6. **9 EMA / VWAP Cross Arrows**
- Plots up/down arrows when the 9 EMA crosses above or below the VWAP.
- Arrow colors and visibility are configurable.
#### 7. **Dynamic Labels**
- On the most recent bar, displays labels for each enabled line (EMAs, VWAP), offset to the right for clarity.
- Labels include the timeframe, type, and current value.
### Customization Options
- **Visibility:** Each plot (line, cloud, arrow, label) can be individually toggled on/off.
- **Colors:** All lines, clouds, and arrows can be colored to user preference, including opacity for clouds.
- **Timeframes:** JLines and EMAs can be calculated on different timeframes, including a custom one.
- **Label Text:** Labels dynamically reflect current indicator values and are color-coded to match their lines.
### Technical Implementation Highlights
- **Helper Functions:** Functions abstract away the logic for multi-timeframe EMA calculation.
- **Security Calls:** Uses `request.security` to fetch data from other timeframes, ensuring accurate multi-timeframe plotting.
- **Efficient Label Management:** Deletes old labels and creates new ones only on the last bar to avoid clutter and maintain performance.
- **Conditional Plotting:** All visual elements are conditionally plotted based on user input, making the indicator highly flexible.
### Use Cases
- **Trend Identification:** Multiple EMAs and VWAP help traders quickly identify trend direction and strength across timeframes.
- **Support/Resistance:** 200 EMA and JLines often act as dynamic support/resistance levels.
- **Entry/Exit Signals:** Crosses between 9 EMA and VWAP, as well as 5/15 EMA clouds, can signal potential trade entries or exits.
- **Pattern Recognition:** Inside bar highlights aid in spotting consolidation and breakout patterns.
### Summary Table of Configurable Elements
| Feature | Timeframes | Cloud Option | Label Option | Color Customizable | Description |
|----------------------------|-------------------|--------------|--------------|--------------------|-----------------------------------------------|
| JLines (72/89 EMA) | 1m, 3m, 5m, 1h, Custom | Yes | Yes | Yes | Key trend-following EMAs with cloud fill |
| 200 EMA | 1m, 3m, 5m, 15m, 1h | No | Yes | Yes | Long-term trend indicator |
| 9 EMA | Any | No | Yes | Yes | Short-term trend indicator |
| VWAP | Chart TF | No | Yes | Yes | Volume-weighted average price |
| 5/15 EMA Cloud (5m) | 5m | Yes | No | Yes | Bullish/bearish cloud between 5/15 EMAs |
| Inside Bar Highlight | Chart TF | No | N/A | Yes | Highlights price consolidation |
| 9 EMA / VWAP Cross Arrows | Chart TF | No | N/A | Yes | Marks EMA/VWAP crossovers with arrows |
This script is ideal for traders seeking a robust, multi-timeframe overlay that combines trend, momentum, and pattern signals in a single, highly customizable indicator. I do not advocate to subscribe to JTrades or the system they tout. This is based on my own observations and not a copy of any JTrades scripts. It is open source to allow full transparency.
Daily Percent Change LabelDaily Percent Change Label
Overview
This Pine Script displays the percentage change from the previous day's closing price as a text label near the current price level on the chart. It works seamlessly across any timeframe (daily, hourly, minute charts) by referencing the daily chart's previous close, making it perfect for traders tracking daily performance.
The label is displayed with a semi-transparent background (green for positive changes, red for negative changes) and white text, ensuring a clean and readable appearance.
Features
Accurate Daily Percent Change: Calculates the percentage change based on the previous day's closing price, even on intraday timeframes (e.g., 1-hour, 5-minute).
Dynamic Label: Shows the percentage change as a label aligned with the current price, updating in real-time.
Color-Coded Background: Semi-transparent green background for positive changes and red for negative changes.
Customizable: Adjust label position, size, color, and style to fit your preferences.
Minimal Impact: No additional plots or graphs, keeping the chart uncluttered.
How to Use
Add the Script:
Copy and paste the script into the Pine Editor in TradingView.
Click "Add to Chart" to apply it.
Check the Output:
A text label (e.g., "+2.34%" or "-1.56%") appears near the current price with a semi-transparent background.
The label is colored green (positive) or red (negative) and updates in real-time.
Switch Timeframes:
Works on any timeframe. The percentage change is always calculated relative to the previous day's close.
Customization Options
Modify the label.new function to customize the label:
Label Position:
Change style=label.style_label_left to label.style_label_right or label.style_label_down to adjust label placement.
Adjust bar_index with an offset (e.g., bar_index + 1) to move the label horizontally.
Text Color:
Modify textcolor=color.white to another color (e.g., color.rgb(255, 255, 0) for yellow).
Background Color:
Adjust color=percent_change >= 0 ? color.new(color.green, 50) : color.new(color.red, 50) to change transparency (e.g., color.new(color.green, 0) for no transparency).
Text Size:
Change size=size.normal to size.small or size.large for smaller or larger text.
Code Details
Timeframe Handling: Uses request.security with the "D" timeframe to fetch the previous day's closing price, ensuring accuracy on intraday charts.
Performance: Updates only on the last bar (barstate.islast) for optimal performance.
Dynamic Styling: Background color changes based on the direction of the price change.
Notes
The label is positioned near the current price for easy reference. To move it closer to the Y-axis, adjust the bar_index offset.
For different reference points (e.g., weekly close), modify the request.security timeframe (e.g., "W" for weekly).
Ensure the script is copied correctly without extra spaces or characters. Use a plain text editor (e.g., Notepad) for copying.
Feedback
Please share your feedback or customizations in the comments! If you find this script helpful, give it a thumbs-up or let others know how you're using it. Happy trading!
Anchored Darvas Box## ANCHORED DARVAS BOX
---
### OVERVIEW
**Anchored Darvas Box** lets you drop a single timestamp on your chart and build a Darvas-style consolidation zone forward from that exact candle. The indicator freezes the first user-defined number of bars to establish the range, verifies that price respects that range for another user-defined number of bars, then waits for the first decisive breakout. The resulting rectangle captures every tick of the accumulation phase and the exact moment of expansion—no manual drawing, complete timestamp precision.
---
### HISTORICAL BACKGROUND
Nicolas Darvas’s 1950s box theory tracked institutional accumulation by hand-drawing rectangles around tight price ranges. A trade was triggered only when price escaped the rectangle.
The anchored version preserves Darvas’s logic but pins the entire sequence to a user-chosen candle: perfect for analysing a market open, an earnings release, FOMC minute, or any other catalytic bar.
---
### ALGORITHM DETAIL
1. **ANCHOR BAR**
*You provide a timestamp via the settings panel.* The script waits until the chart reaches that bar and records its index as **startBar**.
2. **RANGE DEFINITION — BARS 1-7**
• `rangeHigh` = highest high of bars 1-7 plus optional tolerance.
• `rangeLow` = lowest low of bars 1-7 minus optional tolerance.
3. **RANGE VALIDATION — BARS 8-14**
• Price must stay inside ` `.
• Any violation aborts the test; no box is created.
4. **ARMED STATE**
• If bars 8-14 hold the range, two live guide-lines appear:
– **Green** at `rangeHigh`
– **Red** at `rangeLow`
• The script is now “armed,” waiting indefinitely for the first true breakout.
5. **BREAKOUT & BOX CREATION**
• **Up breakout** =`high > rangeHigh` → rectangle drawn in **green**.
• **Down breakout**=`low < rangeLow` → rectangle drawn in **red**.
• Box extends from **startBar** to the breakout bar and never updates again.
• Optional labels print the dollar and percentage height of the box at its left edge.
6. **OPTIONAL COOLDOWN**
• After the box is painted the script can stay silent for a user-defined number of bars, letting you study the fallout without another range immediately arming on top of it.
---
### INPUT PARAMETERS
• **ANCHOR TIME** – Precise yyyy-mm-dd HH:MM:SS that seeds the sequence.
• **BARS TO DEFINE RANGE** – Default 7; affects both definition and validation windows.
• **OPTIONAL TOLERANCE** – Absolute price buffer to ignore micro-wicks.
• **COOLDOWN BARS AFTER BREAKOUT** – Pause length before the indicator is allowed to re-anchor (set to zero to disable).
• **SHOW BOX DISTANCE LABELS** – Toggle to print Δ\$ and Δ% on every completed box.
---
### USER WORKFLOW
1. Add the indicator, open settings, and set **ANCHOR TIME** to the candle you care about (e.g., “2025-04-23 09:30:00” for NYSE open).
2. Watch live as the script:
– Paints the seven-bar range.
– Draws validation lines.
– Locks in the box on breakout.
3. Use the box boundaries as structural stops, targets, or context for further trades.
---
### PRACTICAL APPLICATIONS
• **OPENING RANGE BREAKOUTS** – Anchor at the first second of the session; capture the initial 7-bar range and trade the first clean break.
• **EVENT STUDIES** – Anchor at a news candle to measure immediate post-event volatility.
• **VOLUME PROFILE FUSION** – Combine the anchored box with VPVR to see if the breakout occurs at a high-volume node or a low-liquidity pocket.
• **RISK DISCIPLINE** – Stop-loss can sit just inside the opposite edge of the anchored range, enforcing objective risk.
---
### ADVANCED CUSTOMISATION IDEAS
• **MULTIPLE ANCHORS** – Clone the indicator and anchor several boxes (e.g., London open, New York open).
• **DYNAMIC WINDOW** – Switch the 7-bar fixed length to a volatility-scaled length (ATR percentile).
• **STRATEGY WRAPPER** – Turn the indicator into a `strategy{}` script and back-test anchored boxes on decades of data.
---
### FINAL THOUGHTS
Anchored Darvas Boxes give you Darvas’s timeless range-break methodology anchored to any candle of interest—perfect for dissecting openings, economic releases, or your own bespoke “important” bars with laboratory precision.
Combined EMA/Smiley & DEM System## 🔷 General Overview
This script creates an advanced technical analysis system for TradingView, combining multiple Exponential Moving Averages (EMAs), Simple Moving Averages (SMAs), dynamic Fibonacci levels, and ATR (Average True Range) analysis. It presents the results clearly through interactive, real-time tables directly on the chart.
---
## 🔹 Indicator Structure
The script consists of two main parts:
### **1. EMA & SMA Combined System with Fibonacci**
- **Purpose:**
Provides visual insights by comparing multiple EMA/SMA periods and identifying significant dynamic price levels using Fibonacci ratios around a calculated "Golden" line.
- **Components:**
- **Moving Averages (MAs)**:
- 20 EMAs (periods from 20 to 400)
- 20 SMAs (also from 20 to 400)
- **Golden Line:**
Calculated as the average of all EMAs and SMAs.
- **Dynamic Fibonacci Levels:**
Key ratios around the Golden line (0.5, 0.618, 0.786, 1.0, 1.272, 1.414, 1.618, 2.0) dynamically adjust based on market conditions.
- **Fibonacci Labels:**
Labels are shown next to Fibonacci lines, indicating their numeric value clearly on the chart.
- **Table (Top Right Corner):**
- Displays:
- **Input:** EMA/SMA periods sorted by their current average price levels.
- **AVG:** The average of corresponding EMA & SMA pairs.
- **EMA & SMA Values:** Individual EMA/SMA values clearly marked.
- **Dynamic Highlighting:** Highlights the row whose average (EMA+SMA)/2 is closest to the current price, helping identify immediate price action significance.
- **Sorting Logic:**
Each EMA/SMA pair is dynamically sorted based on their average values. Color coding (red/green) is used:
- **Green:** EMA/SMA pairs with shorter periods when their average is lower.
- **Red:** EMA/SMA pairs with longer periods when their average is lower.
- **Star (⭐):** Represents the "Golden" average clearly.
---
### **2. DEM System (Dynamic EMA/ATR Metrics)**
- **Purpose:**
Provides detailed ATR statistics to assess market volatility clearly and quickly.
- **Components:**
- **Moving Averages:**
- SMA lines: 25, 50, 100, 200.
- **Bollinger Bands:**
- Based on 20-period SMA of highs and standard deviation of lows.
- **ATR Analysis:**
- ATR calculations for multiple periods (1-day, 10, 20, 30, 40, 50).
- **ATR Premium:** Average ATR of all calculated periods, providing an overarching volatility indicator.
- **ATR Table (Bottom Right Corner):**
- Displays clearly structured ATR values and percentages relative to the current close price:
- Columns: **ATR Period**, **Value**, and **% of Close**.
- Rows: Each specific ATR (1D, 10, 20, 30, 40, 50), plus ATR premium.
- The ATR premium is highlighted in yellow to signify its importance clearly.
---
## 🔹 Key Features and Logic Explained
- **Dynamic EMA/SMA Sorting:**
The script computes the average of each EMA/SMA pair and sorts them dynamically on each bar, highlighting their relative importance visually. This allows traders to easily interpret the strength of current support/resistance levels based on moving averages.
- **Closest EMA/SMA Pair to Current Price:**
Calculates the absolute difference between the current price and all EMA/SMA averages, highlighting the closest one for quick reference.
- **Fibonacci Ratios:**
- Dynamically calculated Fibonacci levels based on the "Golden" EMA/SMA average give clear visual guidance for potential targets, supports, and resistances.
- Labels are continuously updated and placed next to levels for clarity.
- **ATR Volatility Analysis:**
- Provides immediate insight into market volatility with absolute and relative (percentage-based) ATR values.
- ATR premium summarizes volatility across multiple timeframes clearly.
---
## 🔹 Practical Use Case:
- Traders can quickly identify support/resistance and critical price zones through EMA/SMA and Fibonacci combinations.
- Useful in assessing immediate volatility, guiding stop-loss and take-profit levels through detailed ATR metrics.
- The dynamic highlighting in tables provides intuitive, real-time decision support for active traders.
---
## 🔹 How to Use this Script:
1. **Adjust EMA & SMA Lengths** from indicator settings if different periods are preferred.
2. **Monitor dynamic Fibonacci levels** around the "Golden" average to identify possible reversal or continuation points.
3. **Check EMA/SMA table:** Rows highlighted indicate immediate significance concerning current market price.
4. **ATR table:** Use volatility metrics for better risk management.
---
## 🔷 Conclusion
This advanced Pine Script indicator efficiently combines multiple EMAs, SMAs, dynamic Fibonacci retracement levels, and volatility analysis using ATR into a comprehensive real-time analytical tool, enhancing traders' decision-making capabilities by providing clear and actionable insights directly on the TradingView chart.
Transient Impact Model [ScorsoneEnterprises]This indicator is an implementation of the Transient Impact Model. This tool is designed to show the strength the current trades have on where price goes before they decay.
Here are links to more sophisticated research articles about Transient Impact Models than this post arxiv.org and arxiv.org
The way this tool is supposed to work in a simple way, is when impact is high price is sensitive to past volume, past trades being placed. When impact is low, it moves in a way that is more independent from past volume. In a more sophisticated system, perhaps transient impact should be calculated for each trade that is placed, not just the total volume of a past bar. I didn't do it to ensure parameters exist and aren’t na, as well as to have more iterations for optimization. Note that the value will change as volume does, as soon as a new candle occurs with no volume, the values could be dramatically different.
How it works
There are a few components to this script, so we’ll go into the equation and then the other functions used in this script.
// Transient Impact Model
transient_impact(params, price_change, lkb) =>
alpha = array.get(params, 0)
beta = array.get(params, 1)
lambda_ = array.get(params, 2)
instantaneous = alpha * volume
transient = 0.0
for t = 1 to lkb - 1
if na(volume )
break
transient := transient + beta * volume * math.exp(-lambda_ * t)
predicted_change = instantaneous + transient
math.pow(price_change - predicted_change, 2)
The parameters alpha, beta, and lambda all represent a different real thing.
Alpha (α):
Represents the instantaneous impact coefficient. It quantifies the immediate effect of the current volume on the price change. In the equation, instantaneous = alpha * volume , alpha scales the current bar's volume (volume ) to determine how much of the price change is due to immediate market impact. A larger alpha suggests that current volume has a stronger instantaneous influence on price.
Beta (β):
Represents the transient impact coefficient.It measures the lingering effect of past volumes on the current price change. In the loop calculating transient, beta * volume * math.exp(-lambda_ * t) shows that beta scales the volume from previous bars (volume ), contributing to a decaying effect over time. A higher beta indicates a stronger influence from past volumes, though this effect diminishes with time due to the exponential decay factor.
Lambda (λ):
Represents the decay rate of the transient impact.It controls how quickly the influence of past volumes fades over time in the transient component. In the term math.exp(-lambda_ * t), lambda determines the rate of exponential decay, where t is the time lag (in bars). A larger lambda means the impact of past volumes decays faster, while a smaller lambda implies a longer-lasting effect.
So in full.
The instantaneous term, alpha * volume , captures the immediate price impact from the current volume.
The transient term, sum of beta * volume * math.exp(-lambda_ * t) over the lookback period, models the cumulative, decaying effect of past volumes.
The total predicted_change combines these two components and is compared to the actual price change to compute an error term, math.pow(price_change - predicted_change, 2), which the script minimizes to optimize alpha, beta, and lambda.
Other parts of the script.
Objective function:
This is a wrapper function with a function to minimize so we get the best alpha, beta, and lambda values. In this case it is the Transient Impact Function, not something like a log-likelihood function, helps with efficiency for a high iteration count.
Finite Difference Gradient:
This function calculates the gradient of the objective function we spoke about. The gradient is like a directional derivative. Which is like the direction of the rate of change. Which is like the direction of the slope of a hill, we can go up or down a hill. It nudges around the parameter, and calculates the derivative of the parameter. The array of these nudged around parameters is what is returned after they are optimized.
Minimize:
This is the function that actually has the loop and calls the Finite Difference Gradient each time. Here is where the minimizing happens, how we go down the hill. If we are below a tolerance, we are at the bottom of the hill.
Applied
After an initial guess, we optimize the parameters and get the transient impact value. This number is huge, so we apply a log to it to make it more readable. From here we need some way to tell if the value is low or high. We shouldn’t use standard deviation because returns are not normally distributed, an IQR is similar and better for non normal data. We store past transient impact values in an array, so that way we can see the 25th and 90th percentiles of the data as a rolling value. If the current transient impact is above the 90th percentile, it is notably high. If below the 25th percentile, notably low. All of these values are plotted so we can use it as a tool.
Tool examples:
The idea around it is that when impact is low, there is room for big money to get size quickly and move prices around.
Here we see the price reacting in the IQR Bands. We see multiple examples where the value above the 90th percentile, the red line, corresponds to continuations in the trend, and below the 25th percentile, the purple line, corresponds to reversals. There is no guarantee these tools will be perfect, that is outlined in these situations, however there is clearly a correlation in this tool and trend.
This tool works on any timeframe, daily as we saw before, or lower like a two minute. The bands don’t represent a direction, like bullish or bearish, we need to determine that by interpreting price action. We see at open and at close there are the highest values for the transient impact. This is to be expected as these are the times with the highest volume of the trading day.
This works on futures as well as equities with the same context. Volume can be attributed to volatility as well. In volatile situations, more volatility comes in, and we can perceive it through the transient impact value.
Inputs
Users can enter the lookback value.
No tool is perfect, the transient impact value is also not perfect and should not be followed blindly. It is good to use any tool along with discretion and price action.
VIX bottom/top with color scale [Ox_kali]📊 Introduction
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The “VIX Bottom/Top with Color Scale” script is designed to provide an intuitive, color-coded visualization of the VIX (Volatility Index), helping traders interpret market sentiment and volatility extremes in real time.
It segments the VIX into clear threshold zones, each associated with a specific market condition—ranging from fear to calm—using a dynamic color-coded system.
This script offers significant value for the following reasons:
Intuitive Risk Interpretation: Color-coded zones make it easy to interpret market sentiment at a glance.
Dynamic Trend Detection: A 200-period SMA of the VIX is plotted and dynamically colored based on trend direction.
Customization and Flexibility: All colors are editable in the parameters panel, grouped under “## Color parameters ##”.
Visual Clarity: Key thresholds are marked with horizontal lines for quick reference.
Practical Trading Tool: Helps identify high-risk and low-risk environments based on volatility levels.
🔍 Key Indicators
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VIX (CBOE Volatility Index) : Measures market volatility and investor fear.
SMA 200 : Long-term trendline of the VIX, with color-coded direction (green = uptrend, red = downtrend).
Color-coded VIX Levels:
🔴 33+ → Something bad just happened
🟠 23–33 → Something bad is happening
🟡 17–23 → Something bad might happen
🟢 14–17 → Nothing bad is happening
✅ 12–14 → Nothing bad will ever happen
🔵 <12 → Something bad is going to happen
🧠 Originality and Purpose
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Unlike traditional VIX indicators that only plot a line, this script enhances interpretation through visual segmentation and dynamic trend tracking.
It serves as a risk-awareness tool that transforms the VIX into a simple, emotional market map.
This is the first version of the script, and future updates may include alerts, background fills, and more advanced features.
⚙️ How It Works
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The script maps the current VIX value to a range and applies the corresponding color.
It calculates a SMA 200 and colors it green or red depending on its slope.
It displays horizontal dotted lines at key thresholds (12, 14, 17, 23, 33).
All colors are configurable via input parameters under the group: "## Color parameters ##".
🧭 Indicator Visualization and Interpretation
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The VIX line changes color based on market condition zones.
The SMA line shows long-term direction with dynamic color.
Horizontal threshold lines visually mark the transitions between volatility zones.
Ideal for quickly identifying periods of fear, caution, or stability.
🛠️ Script Parameters
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Grouped under “## Color parameters ##”, the following elements are customizable:
🎨 VIX Zone Colors:
33+ → Red
23–33 → Orange
17–23 → Yellow
14–17 → Light Green
12–14 → Dark Green
<12 → Blue
📈 SMA Colors:
Uptrend → Green
Downtrend → Red
These settings allow users to match the script’s visuals to their preferred chart style or theme.
✅ Conclusion
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The “VIX Bottom/Top with Color Scale” is a clean, powerful script designed to simplify how traders view volatility.
By combining long-term trend data with real-time color-coded sentiment analysis, this script becomes a go-to reference for managing risk, timing trades, or simply staying in tune with market mood.
🧪 Notes
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This is version 1 of the script. More features such as alert conditions, background fill, and dashboard elements may be added soon. Feedback is welcome!
💡 Color code concept inspired by the original VIX interpretation chart by @nsquaredvalue on Twitter. Big thanks for the visual clarity! 💡
⚠️ Disclaimer
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This script is a visual tool designed to assist in market analysis. It does not guarantee future performance and should be used in conjunction with proper risk management. Past performance is not indicative of future results.
Bitcoin Polynomial Regression ModelThis is the main version of the script. Click here for the Oscillator part of the script.
💡Why this model was created:
One of the key issues with most existing models, including our own Bitcoin Log Growth Curve Model , is that they often fail to realistically account for diminishing returns. As a result, they may present overly optimistic bull cycle targets (hence, we introduced alternative settings in our previous Bitcoin Log Growth Curve Model).
This new model however, has been built from the ground up with a primary focus on incorporating the principle of diminishing returns. It directly responds to this concept, which has been briefly explored here .
📉The theory of diminishing returns:
This theory suggests that as each four-year market cycle unfolds, volatility gradually decreases, leading to more tempered price movements. It also implies that the price increase from one cycle peak to the next will decrease over time as the asset matures. The same pattern applies to cycle lows and the relationship between tops and bottoms. In essence, these price movements are interconnected and should generally follow a consistent pattern. We believe this model provides a more realistic outlook on bull and bear market cycles.
To better understand this theory, the relationships between cycle tops and bottoms are outlined below:https://www.tradingview.com/x/7Hldzsf2/
🔧Creation of the model:
For those interested in how this model was created, the process is explained here. Otherwise, feel free to skip this section.
This model is based on two separate cubic polynomial regression lines. One for the top price trend and another for the bottom. Both follow the general cubic polynomial function:
ax^3 +bx^2 + cx + d.
In this equation, x represents the weekly bar index minus an offset, while a, b, c, and d are determined through polynomial regression analysis. The input (x, y) values used for the polynomial regression analysis are as follows:
Top regression line (x, y) values:
113, 18.6
240, 1004
451, 19128
655, 65502
Bottom regression line (x, y) values:
103, 2.5
267, 211
471, 3193
676, 16255
The values above correspond to historical Bitcoin cycle tops and bottoms, where x is the weekly bar index and y is the weekly closing price of Bitcoin. The best fit is determined using metrics such as R-squared values, residual error analysis, and visual inspection. While the exact details of this evaluation are beyond the scope of this post, the following optimal parameters were found:
Top regression line parameter values:
a: 0.000202798
b: 0.0872922
c: -30.88805
d: 1827.14113
Bottom regression line parameter values:
a: 0.000138314
b: -0.0768236
c: 13.90555
d: -765.8892
📊Polynomial Regression Oscillator:
This publication also includes the oscillator version of the this model which is displayed at the bottom of the screen. The oscillator applies a logarithmic transformation to the price and the regression lines using the formula log10(x) .
The log-transformed price is then normalized using min-max normalization relative to the log-transformed top and bottom regression line with the formula:
normalized price = log(close) - log(bottom regression line) / log(top regression line) - log(bottom regression line)
This transformation results in a price value between 0 and 1 between both the regression lines. The Oscillator version can be found here.
🔍Interpretation of the Model:
In general, the red area represents a caution zone, as historically, the price has often been near its cycle market top within this range. On the other hand, the green area is considered an area of opportunity, as historically, it has corresponded to the market bottom.
The top regression line serves as a signal for the absolute market cycle peak, while the bottom regression line indicates the absolute market cycle bottom.
Additionally, this model provides a predicted range for Bitcoin's future price movements, which can be used to make extrapolated predictions. We will explore this further below.
🔮Future Predictions:
Finally, let's discuss what this model actually predicts for the potential upcoming market cycle top and the corresponding market cycle bottom. In our previous post here , a cycle interval analysis was performed to predict a likely time window for the next cycle top and bottom:
In the image, it is predicted that the next top-to-top cycle interval will be 208 weeks, which translates to November 3rd, 2025. It is also predicted that the bottom-to-top cycle interval will be 152 weeks, which corresponds to October 13th, 2025. On the macro level, these two dates align quite well. For our prediction, we take the average of these two dates: October 24th 2025. This will be our target date for the bull cycle top.
Now, let's do the same for the upcoming cycle bottom. The bottom-to-bottom cycle interval is predicted to be 205 weeks, which translates to October 19th, 2026, and the top-to-bottom cycle interval is predicted to be 259 weeks, which corresponds to October 26th, 2026. We then take the average of these two dates, predicting a bear cycle bottom date target of October 19th, 2026.
Now that we have our predicted top and bottom cycle date targets, we can simply reference these two dates to our model, giving us the Bitcoin top price prediction in the range of 152,000 in Q4 2025 and a subsequent bottom price prediction in the range of 46,500 in Q4 2026.
For those interested in understanding what this specifically means for the predicted diminishing return top and bottom cycle values, the image below displays these predicted values. The new values are highlighted in yellow:
And of course, keep in mind that these targets are just rough estimates. While we've done our best to estimate these targets through a data-driven approach, markets will always remain unpredictable in nature. What are your targets? Feel free to share them in the comment section below.
Bitcoin Polynomial Regression OscillatorThis is the oscillator version of the script. Click here for the other part of the script.
💡Why this model was created:
One of the key issues with most existing models, including our own Bitcoin Log Growth Curve Model , is that they often fail to realistically account for diminishing returns. As a result, they may present overly optimistic bull cycle targets (hence, we introduced alternative settings in our previous Bitcoin Log Growth Curve Model).
This new model however, has been built from the ground up with a primary focus on incorporating the principle of diminishing returns. It directly responds to this concept, which has been briefly explored here .
📉The theory of diminishing returns:
This theory suggests that as each four-year market cycle unfolds, volatility gradually decreases, leading to more tempered price movements. It also implies that the price increase from one cycle peak to the next will decrease over time as the asset matures. The same pattern applies to cycle lows and the relationship between tops and bottoms. In essence, these price movements are interconnected and should generally follow a consistent pattern. We believe this model provides a more realistic outlook on bull and bear market cycles.
To better understand this theory, the relationships between cycle tops and bottoms are outlined below:https://www.tradingview.com/x/7Hldzsf2/
🔧Creation of the model:
For those interested in how this model was created, the process is explained here. Otherwise, feel free to skip this section.
This model is based on two separate cubic polynomial regression lines. One for the top price trend and another for the bottom. Both follow the general cubic polynomial function:
ax^3 +bx^2 + cx + d.
In this equation, x represents the weekly bar index minus an offset, while a, b, c, and d are determined through polynomial regression analysis. The input (x, y) values used for the polynomial regression analysis are as follows:
Top regression line (x, y) values:
113, 18.6
240, 1004
451, 19128
655, 65502
Bottom regression line (x, y) values:
103, 2.5
267, 211
471, 3193
676, 16255
The values above correspond to historical Bitcoin cycle tops and bottoms, where x is the weekly bar index and y is the weekly closing price of Bitcoin. The best fit is determined using metrics such as R-squared values, residual error analysis, and visual inspection. While the exact details of this evaluation are beyond the scope of this post, the following optimal parameters were found:
Top regression line parameter values:
a: 0.000202798
b: 0.0872922
c: -30.88805
d: 1827.14113
Bottom regression line parameter values:
a: 0.000138314
b: -0.0768236
c: 13.90555
d: -765.8892
📊Polynomial Regression Oscillator:
This publication also includes the oscillator version of the this model which is displayed at the bottom of the screen. The oscillator applies a logarithmic transformation to the price and the regression lines using the formula log10(x) .
The log-transformed price is then normalized using min-max normalization relative to the log-transformed top and bottom regression line with the formula:
normalized price = log(close) - log(bottom regression line) / log(top regression line) - log(bottom regression line)
This transformation results in a price value between 0 and 1 between both the regression lines.
🔍Interpretation of the Model:
In general, the red area represents a caution zone, as historically, the price has often been near its cycle market top within this range. On the other hand, the green area is considered an area of opportunity, as historically, it has corresponded to the market bottom.
The top regression line serves as a signal for the absolute market cycle peak, while the bottom regression line indicates the absolute market cycle bottom.
Additionally, this model provides a predicted range for Bitcoin's future price movements, which can be used to make extrapolated predictions. We will explore this further below.
🔮Future Predictions:
Finally, let's discuss what this model actually predicts for the potential upcoming market cycle top and the corresponding market cycle bottom. In our previous post here , a cycle interval analysis was performed to predict a likely time window for the next cycle top and bottom:
In the image, it is predicted that the next top-to-top cycle interval will be 208 weeks, which translates to November 3rd, 2025. It is also predicted that the bottom-to-top cycle interval will be 152 weeks, which corresponds to October 13th, 2025. On the macro level, these two dates align quite well. For our prediction, we take the average of these two dates: October 24th 2025. This will be our target date for the bull cycle top.
Now, let's do the same for the upcoming cycle bottom. The bottom-to-bottom cycle interval is predicted to be 205 weeks, which translates to October 19th, 2026, and the top-to-bottom cycle interval is predicted to be 259 weeks, which corresponds to October 26th, 2026. We then take the average of these two dates, predicting a bear cycle bottom date target of October 19th, 2026.
Now that we have our predicted top and bottom cycle date targets, we can simply reference these two dates to our model, giving us the Bitcoin top price prediction in the range of 152,000 in Q4 2025 and a subsequent bottom price prediction in the range of 46,500 in Q4 2026.
For those interested in understanding what this specifically means for the predicted diminishing return top and bottom cycle values, the image below displays these predicted values. The new values are highlighted in yellow:
And of course, keep in mind that these targets are just rough estimates. While we've done our best to estimate these targets through a data-driven approach, markets will always remain unpredictable in nature. What are your targets? Feel free to share them in the comment section below.
Wave N + KDJ + Volumi + SMC + IchimokuWave N + KDJ + Volume + SMC + Ichimoku Indicator
Overview
This script is a multi-layered technical indicator designed to provide traders with enhanced market insights by combining five key methodologies:
• Wave N Pattern (Price Action)
• KDJ Oscillator (Momentum)
• Volume Filtering (Confirmation)
• Smart Money Concepts (Order Blocks) (Institutional Activity)
• Ichimoku Cloud (Trend and Support/Resistance)
By integrating these components, the indicator identifies high-probability trading signals, early warnings of trend shifts, and institutional price zones to improve decision-making in volatile markets.
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How It Works
1️⃣ Wave N Pattern (Price Action Structure)
The Wave N pattern is a classic price action formation that helps spot potential trend reversals and continuations:
• A Bullish Wave N is detected when a higher low and a higher high structure appears.
• A Bearish Wave N is detected when a lower high and a lower low structure forms.
2️⃣ KDJ Oscillator (Momentum & Trend Strength)
The KDJ Indicator is a variation of the Stochastic Oscillator that adds a third line, J, to amplify sensitivity to trend movements.
• J > 50 indicates bullish momentum.
• J < 50 indicates bearish momentum.
• The script includes an early warning signal when J crosses 50, suggesting a possible trend shift.
3️⃣ Volume Filtering (Trade Confirmation)
To avoid false signals, the script integrates volume confirmation:
• A signal is valid only if the volume is above the 20-period EMA of volume.
• This ensures that trade signals are supported by strong market participation.
4️⃣ Smart Money Concepts (Order Blocks)
Order Blocks represent areas of institutional interest, where large traders accumulate or distribute positions.
• The script detects bullish order blocks (potential support) and bearish order blocks (potential resistance).
• These areas help identify optimal entry and exit points.
5️⃣ Ichimoku Cloud (Trend & Dynamic Support/Resistance)
The Ichimoku Cloud is used to confirm trend direction:
• Baseline (Kijun-sen) acts as a key trend filter.
• Senkou Span A & B form the cloud (Kumo), indicating dynamic support/resistance.
• Buy signals require price to be above the baseline, while sell signals require price to be below the baseline.
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Trading Signals & Visual Elements
✅ BUY Signal (Green Arrow)
Occurs when:
• A Bullish Wave N forms
• J > 50 (Bullish KDJ Signal)
• Volume is above EMA threshold
• Price is above the Ichimoku Baseline
❌ SELL Signal (Red Arrow)
Occurs when:
• A Bearish Wave N forms
• J < 50 (Bearish KDJ Signal)
• Volume is above EMA threshold
• Price is below the Ichimoku Baseline
⚠️ Early Warning (Trend Shift Signal)
• An early warning appears when J crosses 50, indicating a possible upcoming trend shift.
• The line color changes based on the potential move:
• Green/Blue → Possible Uptrend
• Red/Orange → Possible Downtrend
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Why This Indicator is Unique?
Unlike simple trend-following indicators, this script:
• Combines Price Action, Momentum, Volume, and Institutional Order Flow for a multi-dimensional approach.
• Filters out weak signals using volume confirmation and Ichimoku.
• Provides early warnings before major trend shifts.
• Visualizes Smart Money Order Blocks, giving traders an edge in spotting institutional zones.
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Best Timeframes & Markets
📊 Recommended Timeframes:
• 1H & 1D (works best on medium/long-term trends)
💹 Markets:
• Crypto, Forex, and Stocks
This indicator is designed for traders who value confluence and strong confirmation in their strategies. Whether you are a trend trader, swing trader, or institutional flow analyst, this tool can help refine your decision-making process.
🚀 Optimize your trades with Wave N + KDJ + Volume + SMC + Ichimoku! 🚀
Time-based Alerts for Trading Windows🌟 Time-based Alerts for Trading Windows 🌐📈
This is a re-uploaded script as the previous one got hidden.
This Time-based Alerts for Trading Windows script is a highly customizable and reliable tool designed to assist traders in managing automated strategies or manually monitoring specific market conditions. Inspired by CrossTrade's Time-based Alert, this script is tailored for those who rely on precise time windows to trigger actions, such as sending webhook signals or managing Expert Advisors (EAs).
Whether you are a scalper, day trader, or algorithmic trader, this script empowers you to stay on top of your trades with fully customizable time-based alerts.
🛠️ Customizable Time Alerts
This indicator allows you to create up to 12 unique time windows by specifying the exact hour and minute for each alert. Each time window corresponds to an individual alert condition, making it perfect for managing trades during specific market sessions or key time periods.
For example:
Alert 1 can be set at 9:30 AM (market open).
Alert 2 can be set at 3:55 PM (just before market close).
Each alert can be toggled on or off in the indicator settings, allowing you to manage alerts without having to reconfigure your script.
You can adjust the colours to fit any colour scheme you like!
🕒 Odd and Even Time Alerts
The script comes with three built-in alert type categories:
Odd Alerts (marked with a green triangle on the chart): These correspond to odd-numbered inputs like Alert 1, Alert 3, Alert 5, and so on.
Even Alerts (marked with a red triangle on the chart): These correspond to even-numbered inputs like Alert 2, Alert 4, Alert 6, and so on.
You can also customize all 12 alerts individually to include a custom alert message
These alerts serve as a convenient way to differentiate between multiple trading strategies or market conditions. You can customize alert messages for odd and even alerts directly from TradingView’s alert panel.
🔗 Webhook Integration for Automation
This script is fully compatible with webhook-based automation. By configuring your alerts in TradingView, you can send signals to trading bots, EAs, or any third-party system. For example, you can:
Turn off an EA at a specific time (e.g., 3:55 PM EST).
Send buy/sell signals to your bot during predefined trading windows.
Simply use TradingView’s alert message editor to format webhook payloads for your automation system.
🌐 Timezone Flexibility
Trading happens across multiple time zones, and this script accounts for that. You can toggle between:
Eastern Time (New York): Ideal for most US-based markets.
Central Time (Exchange): Useful for futures and commodities traders.
This ensures your alerts are always in sync with your preferred time zone, eliminating confusion.
🎨 Visual Indicators
The script plots visual markers directly on your chart to indicate active alerts:
Up Facing Triangles: Represent odd-numbered alerts, providing a quick reference for these time windows.
Down Facing Triangles: Represent even-numbered alerts, helping you track different strategies or conditions.
These visual markers make it easy to see when alerts are triggered, even at a glance.
📈 Practical Use Case
Let’s say you’re trading the USTEC index on a 1-minute chart. You want to:
Turn off your trading bot at 16:55 EST to avoid after-market volatility.
Trigger a re-entry signal at 17:30 EST to capture moves during the Asian session.
Visually monitor these actions on your chart for easy reference.
This script makes it possible with precision alerts and webhook integration. Simply configure the time windows in the settings and set up your alerts in TradingView.
🚨 How to Set Up Alerts
Enable or Disable Alerts: Use the script’s settings to toggle specific alerts on or off as needed.
Set Custom Time Windows: Define the hour and minute for each alert in the settings panel.
Create Alerts in TradingView:
Go to the TradingView alert panel.
Select the condition (e.g., "Odd Time-based Alert (Green)" or "Even Time-based Alert (Red)").
Customize the alert message for webhook integration or personal notification.
Choose the trigger type: Once Per Bar or Once Per Bar Close to keep the alert active.
Integrate with Webhooks: Use the alert message field to format payloads for automation systems like MT4, MT5, or third-party bots.
📋 Key Notes
Alerts can trigger indefinitely if set to "Once Per Bar" or "Once Per Bar Close".
Always ensure the expiration date is set far in the future to avoid unexpected alert deactivation.
Test webhook messages and alert configurations thoroughly before using them in live trading.
This script is a powerful addition to your trading toolbox, offering precision, flexibility, and automation capabilities. Whether you’re turning off an EA, managing trades during market sessions, or automating strategies via webhooks, this script is here to support you.
Start using the Time-based Alerts for Trading Windows today and trade with confidence! 🚀✨
